People, Institutions, and Pixels: Linking Remote Sensing and Social Science to Understand Social Adaptation to Environmental Change.

This research presents an interdisciplinary approach, which links theories from grassland ecology and institutional economics and methods from remote sensing, field ecological measurements, household survey, statistical modeling, and agent-based computational modeling, to study the dynamics of grassland social-ecological systems on the Mongolian plateau, including Mongolia and Inner Mongolia Autonomous Region, China, and social adaptation to climate change and ecosystem degradation. A range of research questions in the fields of remote sensing of vegetation, drivers and mechanisms of resource dynamics, and societal adaptation to environmental change were addressed at regional and local scales. Using a remote sensing based light-use efficiency model, I estimated annual grassland net primary productivity on the Mongolian plateau over the past three decades and analyzed the spatial-temporal dynamics of annual grassland net primary productivity in response to climate variability and change. In order to account for the insufficiency of using multispectral images to map grassland communities and monitor grassland dynamics, especially grassland degradation, I analyzed the potential for using hyperspectral remote sensing to detect the quantity and quality of dominant grassland communities across ecological gradients of the Inner Mongolian grasslands, based on field data collected across a large geographic area. The dynamics of grassland productivity on the Mongolian plateau over the past decades was interpreted both qualitatively and quantitatively. I used spatial panel data models to identify the biophysical and socioeconomic factors driving the interannual dynamics of grassland net primary productivity across agro-ecological zones on the Mongolian plateau over the past three decades. Social adaptations to climate change and grassland degradation on the Mongolian plateau was studied at both household and community levels. A household survey was designed and implemented across ecological gradients of Mongolia (210 households) and Inner Mongolia, China (540 households), to study livelihood adaptation practices of herders to environmental change. Informed by the empirical studies, I built an agent-based computational model to explore social-ecological outcomes of pasture use under alternative institutional (i.e., grazing sedentarization, pasture rental markets, and reciprocal use of pastures) and climatic (i.e., frequencies of climate hazards) scenarios.PHDNatural Resources and EnvironmentUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/97961/1/junw_1.pd

Integrating Herbivore Population Dynamics Into a Global Land Biosphere Model: Plugging Animals Into the Earth System

Mammalian herbivores are an essential component of grassland and savanna ecosystems, and with feedbacks to the climate system. To date, the response and feedbacks of mammalian herbivores to changes in both abiotic and biotic factors are poorly quantified and not adequately represented in the current global land surface modeling framework. In this study, we coupled herbivore population dynamics in a global land model (the Dynamic Land Ecosystem Model, DLEM 3.0) to simulate populations of horses, cattle, sheep, and goats, and their responses to changes in multiple environmental factors at the site level across different continents during 1980–2010. Simulated results show that the model is capable of reproducing observed herbivore population dynamics across all sites for these animal groups. Our simulation results also indicate that during this period, climate extremes led to a maximum mortality of 27% of the total herbivores in Mongolia. Across all sites, herbivores reduced aboveground net primary productivity (ANPP) and heterotrophic respiration (Rh) by 14% and 15%, respectively (p \u3c 0.05). With adequate parameterization, the model can be used for historical assessment and future prediction of mammalian herbivore populations and their relevant impacts on biogeochemical cycles. Our simulation results demonstrate a strong coupling between primary producers and consumers, indicating that inclusion of herbivores into the global land modeling framework is essential to better understand the potentially large effect of herbivores on carbon cycles in grassland and savanna ecosystems

A systematic review on the use of remote sensing technologies in quantifying grasslands ecosystem services

The last decade has seen considerable progress in scientific research on vegetation ecosystem services. While much research has focused on forests and wetlands, grasslands also provide a variety of different provisioning, supporting, cultural, and regulating services. With recent advances in remote sensing technology, there is a possibility that Earth observation data could contribute extensively to research on grassland ecosystem services. This study conducted a systematic review on progress, emerging gaps, and opportunities on the application of remote sensing technologies in quantifying all grassland ecosystem services including those that are related to water. The contribution of biomass, Leaf Area Index (LAI), and Canopy Storage Capacity (CSC) as water-related ecosystem services derived from grasslands was explored. Two hundred and twenty-two peer-reviewed articles from Web of Science, Scopus, and Institute of Electrical and Electronics Engineers were analyzed. About 39% of the studies were conducted in Asia with most of the contributions coming from China while a few studies were from the global south regions such as Southern Africa. Overall, forage provision, climate regulation, and primary production were the most researched grassland ecosystem services in the context of Earth observation data applications. About 39 Earth observation sensors were used in the literature to map grassland ecosystem services and MODIS had the highest utilization frequency. The most widely used vegetation indices for mapping general grassland ecosystem services in literature included the red and near-infrared sections of the electromagnetic spectrum. Remote sensing algorithms used within the retrieved literature include process-based models, machine learning algorithms, and multivariate techniques. For water-related grassland ecosystem services, biomass, CSC, and LAI were the most prominent proxies characterized by remotely sensed data for under-standing evapotranspiration, infiltration, run-off, soil water availability, groundwater restoration and surface water balance. An understanding of such hydrological processes is crucial in providing insights on water redistribution and balance within grassland ecosystems which is important for water management

Integrated desertification assessment in Southern Mongolia

The Bulgan soum in southern Mongolia is a part of the Gobi Three Beauty National Park. The territory is composed of arid and semi-arid desert, encompassing 720 000 ha. A desertification threat, which was virtually unknown for many years, has become a serious environmental problem in the last 20 years. Climatic variations, low variable rainfall, and dust storms overlaid by unsustainable human land-use practices, primarily poorly managed livestock grazing, are contributing to accelerated desertification. The primary objective of this study is to assess desertification based on soil, vegetation, climate and socio-economic indicators including modified soil adjusted vegetation index (MSAVI), topsoil grain size index (GSI), shrinkage of groundwater sources, and extent of sand movement. Those were directly derived from Landsat MSS, TM, and ETM remote sensing images for the growing season months for the years of 1973, 1990, 1991, 2002 and 2005. The results show that the MSAVI is highly correlated to aboveground plant biomass and indicates a general decrease in vegetation biomass, while GSI manifests topsoil coarsening over the last 25 years. In terms of climatic indicators, the historical climate records for the Bulgan soum show warming of approximately 0.7°C over the period 1970 to 2002. Drought occurs once every 2-3 years according to the SPI and Pedi indices (with 50% probability). The frequency of dust storms in the 1987-2002 period was about twice that during the period 1970-1986. There was however, no dust haze after 1994. Plant biomass was largely controlled by low variable rainfall, by dust storms, and temperature. Climate change scenarios, based on results from time series forecasting, indicate future warming by 0.05°C per year (with 37% probability) and by 0.4 dust storm frequencies per year (with 31% probability). It results in a decline of plant biomass of 2 kg ha-1 yr-1 (with 26% probability) that will likely to exacerbate desertification. In terms of the socio-economy of the herders, Chi-square tests show degradation classes to be associated with wealth groups, and the greater the livestock numbers, the greater the degradation. Large family size (triggers large stock numbers), older age, former herding households and decreased livestock moves were the causes of desertification. A time trend forecasting analysis projects an increase in livestock numbers (7000 standard stock units per year), particularly goats. In general, land degradation in the study area increased from 1990 to 2005, and 94% of the area is considered to be degraded to varying degrees. The slightly degraded class covered 12%, the moderate class 44% and the severely degraded class 38% of the Bulgan soum in 2005. Sand encroachments occurred in 35% of the landscape, which have increased by 19% since 1973. 1.7% of total groundwater bodies in 1973 completely disappeared in 2005. Furthermore, the area affected by desertification has increased; the rate of desertification has also accelerated from 1% in the 1990s to 2% in 2005.Integrierte Untersuchungen zur Desertifikation in der südlichen Mongolei Das Gebiet "Bulgan soum" im Süden der Mongolei ist Teil des "Gobi Three Beauty National Park". Es besteht aus ariden und semi-ariden Wüstenbereichen mit einer Fläche von 720 000 ha. In den letzten 20 Jahren ist die Bedrohung durch Desertifikation, früher so gut wie unbekannt, zu einem ernsthaften Umweltproblem geworden. Klimaschwankungen, geringe und stark variierende Niederschläge sowie Staubstürme zusammen mit einer nicht nachhaltigen Landnutzung, hauptsächlich Überweidung, tragen zu der beschleunigten Desertifikation bei. Das Hauptziel dieser Studie ist die Bewertung der Desertifikation auf der Grundlage von Boden-, Vegetations-, Klima- und sozioökonomischen Indikatoren einschließlich des "modified soil adjusted vegetation index (MSAVI), Korngrößenindex des Oberbodens (topsoil grain size index (GSI), Abnahme der Grundwasserressourcen und Ausmaß der Sandbewegung. Diese wurden aus Landsat MSS, TM und ETM Satellitenaufnahmen für die Vegetationsperioden der Jahre 1973, 1990, 1991, 2002 und 2005 entnommen. Die Ergebnisse zeigen, dass MSAVI mit der überirdischen Pflanzenbiomasse stark korreliert und auf eine allgemeine Abnahme der Biomasse hinweist, während der GSI eine Zunahme der gröberen Sandfraktionen während der letzten 25 Jahre deutlich macht. Hinsichtlich klimatischer Indikatoren zeigen die historischen Klimaaufzeichnungen für den Bulgan soum eine Erwärmung von ca. 0.7°C zwischen 1970 und 2002. Die SPI- und Pedi-Indizes weisen auf eine Dürre alle 2 bis 3 Jahre hin (mit 50% Wahrscheinlichkeit). Staubstürme traten 1987 bis 2002 fast doppelt so häufig auf wie im Zeitraum 1970 bis 1986. Nach 1994 gab es jedoch keine Staubdunstereignisse. Pflanzenbiomasse wurde hauptsächlich durch niedrige und variierende Niederschläge, Staubstürme und Temperaturen beeinflusst. Klimawandelszenarien auf der Grundlage von Zeitreihenanalysen prognostizieren eine zukünftige Erwärmung um 0.05°C pro Jahr (mit 37% Wahrscheinlichkeit), sowie eine Zunahme der Staubstürme um 0.4 Sturm pro Jahr (mit 31% Wahrscheinlichkeit), werden zu einer Abnahme der Biomasse um 2 kg ha-1 Jahr-1 (mit 26% Wahrscheinlichkeit) führen und damit voraussichtlich die Desertifikation beschleunigen. Bezogen auf die sozioökonomische Situation der Hirten zeigen die Chi-square test, dass die Degradationsklassen mit Wohlstand korrelieren und, dass je größer die Herden, desto größer die Degradation. Große Familien (= große Herden), höheres Alter, ehemalige Nomaden-Haushalte und geringere Anzahl von Herdenbewegungen führten zu Desertifikation. Zeitreihenanalysen sagen eine Zunahme der Viehzahlen (7000 "standard stock units" pro Jahr), insbesondere von Ziegen, voraus. Die Landdegradation im Untersuchungsraum nahm von 1990 bis 2005 zu, wobei 94% des Gebietes unterschiedlich stark degradiert ist. In 2005 nahmen gering degradierte Bereiche 12%, mäßig degradierte 44% und stark degradierte 38% des Bulgan soum ein. Starkes Vordringen von Sand konnte verzeichnet werden, der 35% der Landschaft bedeckt und um 19% seit 1973 zugenommen hatte. Eine Abnahme des Grundwassers um 1.7% der Grundwassermenge von 1973 wurde verzeichnet. Außerdem hat das durch Desertifikation betroffene Gebiet an Größe zugenommen und auch die Desertifikationsrate hat sich von 1% in den 1990er Jahren auf 2% in 2005 erhöht

Potential Effects of Altered Precipitation Regimes on Primary Production in Terrestrial Ecosystems

In addition to causing an increase in mean temperatures, climate change is also altering precipitation regimes across the globe. General circulation models project both latitude-dependent changes in precipitation mean and increases in precipitation variability. These changes in water availability will impact terrestrial primary productivity, the fixation of carbon dioxide into organic matter by plants. In my thesis, I addressed the following three questions: 1.) What will be the relative effect of changes in the mean and standard deviation of annual precipitation on mean annual primary production? 2.) Which ecosystems will be the most sensitive to changes in precipitation? 3.) Will increases in production variability be disproportionately greater than increases in precipitation variability? I gathered 58 time series of annual precipitation and aboveground net primary production (ANPP) from long-term ecological study sites across the globe. I quantified the sensitivity of ANPP at each site to changes in precipitation mean and variance. My results indicated that mean ANPP is about 40 times more sensitive to changes in precipitation mean than to changes in precipitation variance. I showed that semi-arid ecosystems such as shortgrass steppe in Colorado or typical steppe in Inner Mongolia may be the most sensitive to changes in precipitation mean. At these sites and several others, a 1% change in mean precipitation may result in a change in ANPP that is greater than 1%. To address how increases in interannual precipitation variability will impact the variability of ANPP, I perturbed the variability of observed precipitation time series and evaluated the impact of this perturbation on predicted ANPP variability. I found that different assumptions about the precipitation-ANPP relationship had different implications for how increases in precipitation variability will impact ANPP variability. Increases in ANPP variability were always directly proportional to increases in precipitation variability when ANPP was modeled as a simple linear or a lagged function of precipitation. However, when ANPP was modeled as a nonlinear, saturating function of precipitation, increases in ANPP variability were disproportionately low compared to increases in precipitation variability during wet years but disproportionately high during dry years. My thesis addresses an existing research gap regarding the long-term impact of increases in interannual precipitation variability on key ecosystem functioning. I showed that increases in precipitation variability will have negligible impacts on ANPP mean and have disproportionately large impacts on ANPP variability only when ANPP is a concave down, nonlinear function of precipitation. My work also demonstrates the importance of the precipitation-ANPP relationship in determining the magnitude of impacts to ANPP caused by changes in precipitation. Finally, my thesis highlights the potential for considerable changes in ANPP variability due to increases in precipitation variability

Predicting spatial-temporal patterns of diet quality and large herbivore performance using satellite time series

Adaptive management of large herbivores requires an understanding of how spatial-temporal fluctuations in forage biomass and quality influence animal performance. Advances in remote sensing have yielded information about the spatial-temporal dynamics of forage biomass, which in turn have informed rangeland management decisions such as stocking rate and paddock selection for free-ranging cattle. However, less is known about the spatial-temporal patterns of diet quality and their influence on large herbivore performance. This is due to infrequent concurrent ground observations of forage conditions with performance (e.g., mass gain), and previously limited satellite data at fine spatial and temporal scales. We combined multi-temporal field observations of diet quality (weekly) and mass gain (monthly) with satellite-derived phenological metrics (pseudo-daily, using data fusion and interpolation) to model daily mass gains of free-ranging yearling cattle in shortgrass steppe. We used this model to predict grazing season (mid-May to October) mass gains, a key management indicator, across 40 different paddocks grazed over a 10-year period (n = 138). We found strong relationships between diet quality and the satellite-derived phenological metrics, especially metrics related to the timing and rate of green-up and senescence. Satellite-derived diet quality estimates were strong predictors of monthly mass gains (R2 = 0.68) across a wide range of aboveground net herbaceous production. Season-long predictions of average daily gain and cattle off-mass had mean absolute errors of 8.9% and 2.9%, respectively. The model performed better temporally (across repeated observations in the same paddock) than spatially (across all paddocks within a given year), highlighting the need for accurate vegetation maps and robust field data collection across both space and time. This study demonstrates that freeranging cattle performance in rangelands is strongly affected by diet quality, which is related to the timing of vegetation green-up and senescence. Senescing vegetation suppressed mass gains, even if adequate forage was available. The satellite-based pseudo-daily approach presented here offers new opportunities for adaptive management of large herbivores, such as identifying withinseason triggers to move livestock among paddocks, predicting wildlife herd health, or timing the grazing season to better match earlier spring green-up caused by climate change and plant species invasion

ECOLOGICAL STOICHIOMETRY IN WATERSHEDS: FROM LAND TO WATER IN THE QINGHAI LAKE BASIN

We examined the influences of grassland status (as indexed by normalized difference vegetation index, NDVI) on carbon (C), nitrogen (N), and phosphorus (P) concentrations and stoichiometry, nutrient limitation, as well as microbial community structure in soil, stream, and/or lake ecosystems in the Qinghai Lake watershed, where grassland is the dominant landcover and more than half of the grassland is degraded. Chapter 2 showed that grassland degradation decreased C and N concentrations as well as C:N, C:P, and N:P ratios in soil. Moreover, grassland degradation decreased C, N, and P concentrations and influenced C:N and N:P ratios in soil microbial biomass. Soil microorganisms exhibited strong homeostatic behavior while variations of microbial biomass C:N and N:P ratios suggest changes in microbial activities and community structure. The soil became relatively more P rich and thus N limitation is anticipated to be more apparent with grassland degradation. Chapter 3 provided a picture of potentially differential influences of grassland degradation on DOC, TN, and TP in streamwater. The imbalances of C:N:P stoichiometry between streamwater and biofilms and the non-isometric relationships between biofilm C and P suggest that stream biofilms might be limited by P and sensitive to P variation. Chapter 4 indicated that grassland degradation has the potential to differentially influence the nutrients delivered to streams with substantial increases in P but decreases in N and N:P, alleviating P limitation of stream periphyton and, ultimately, stimulating P-limited phytoplankton growth in the lake. Chapter 5 revealed that grassland degradation shifted bacterial diversity and communities in soil, likely by changing soil moisture, soil organic carbon, total nitrogen, and total phosphorus. Chapter 6 showed that the variation of bacterial communities in stream biofilms was closely associated with rate of change in NDVI, pH, conductivity, as well as C, N, P contents and C:N ratio in biofilms per se. Alpha diversity was positively correlated with C, N, and P in biofilms. Abundant subcommunities of microbes were more strongly associated with environmental variables. Overall, my dissertation revealed strong impacts of grassland degradation on several aspects of nutrient dynamics and limitation as well as on microbial communities in terrestrial and aquatic ecosystems in the Qinghai Lake watershed

Impacts of grazing intensity, precipitation and temperature on productivity, forage quality, species composition and diversity in typical steppe of Inner Mongolia

The overall goal of this study is to analyze and evaluate the long-term effects of sheep grazing intensity on yield performance, herbage quality, species diversity and specie composition in grassland ecosystems in Inner Mongolia, and then to provide efficient practices preventing grassland degradation